David Lewis

Data

Index

Books
Articles
Reports


Books

The Politics of Presidential Appointments: Political Control and Bureaucratic Performance. Princeton, NJ: Princeton University Press (2008).

Chapter 2

Data for Figure 2.1

Chapter 4

Data for Figures 4.2 and 4.3 (Descriptions of variables in sheet 2 of Excel file)

Chapter4PlumDetailBatch.do

Chapter 5

Politicization Over Time Data (1988-2005)
Codebook for Politicization Over Time Data

Time-varying covariates (Merged with Politicization Over Time Data)

Time-varying covariates Codebook

STATA batch file for Chapter 5 analysis

STATA batch file for Chapter 5 analysis (same as Politicization Over Time Data Excel File)

STATA time-varying covariates data for Chapter 5 analysis (same as Time-varying covariates Excel file)

Presidents and the Politics of Agency Design. Stanford, CA: Stanford University Press (2003).

Administrative Agency Insulation Data Set

This is a data set of United States government administrative agencies created between 1946 and 1997. The data were used for all quantitative analysis in the book. Each agency created during this period is 1 observation. The data set excludes advisory, quasi-official, multi-lateral, educational and research agencies, and support offices common to all cabinet departments. An explanation of the data set, how the data was collected, and a description of the variables is included in the codebook below. Stata batch files for the models estimated in chapters 2, 5 are also included below. All users are advised to look at the data update before using the data for new projects. Please report any problems or questions to me.

Administrative Agency Insulation Data (APDesignData)

Code Book (Codebook)

Updates and Notes (UpdateNotes

Stata Batch Files (chapter2.do-chapter5.do)


Agency Creation Count Data

In Chapter 4 I estimate a series of models where the dependent variable is a count of the number of agencies created in the 1946-1995 period. The data set includes a count of the number of agencies created by departmental order, executive order, reorganization plan, and legislation in each year. It also includes a number of independent variables that I used for the models in Chapter 4. Persons interested in examining this data more carefully might also want to look at the data and batch files for “Agencies by Presidential Design” below.

Agency Creation Count Data (agencycountdata)

State Batch File (chapter4.do)


Administrative Agency Insulation Event File

The agency insulation data set above has been expanded for event history analysis. In this expanded data set there are multiple observations for each agency to allow for the inclusion of time-varying covariates in parametric models of agency duration or hazard rates. This means, for example, that an agency created in 1946 and still in existence in 1997 will have 52 observations. In addition to a unique agency identifier and a variable indicating the year of observation, each observation includes the date the observation started, the date the observation ended, and the length of time the agency has been alive. Each observation also includes state variables, 0 for alive, and 1 for terminated. A more complete description of the data is included in the codebook below.

Event File Data Set (APDesignSpellData.xls)

Code Book (Eventfilecodebook)

Articles

“Presidents and Patronage.” (with Gary E. Hollibaugh, Jr. and Gabe Horton), forthcoming, American Journal of Political Science.

For access to data and codebooks see:  http://thedata.harvard.edu/dvn/dv/ajps

“Influencing the Bureaucracy: The Irony of Congressional Oversight,” (with Joshua Clinton and Jennifer L. Selin), forthcoming, American Journal of Political Science.

“Policy Influence, Agency-Specific Expertise, and Exit in the Federal Service,” (with Anthony M. Bertelli). Journal of Public Administration Research and Theory 23(2):223-245 (2013).


“Politics Can Limit Policy Opportunism in Fiscal Institutions: Evidence from Official General Fund Revenue Forecasts in the American States,” (with George A. Krause and James Douglas). Journal of Policy Analysis and Management 32(2):271-95 (2013).


“The Invisible Presidential Appointments: An Examination of Appointments to the Department of Labor, 2001-2011,” (with Richard W. Waterman). Presidential Studies Quarterly 43 (1): 35-57 (2013).


“The Personnel Process in the Modern Presidency,” Presidential Studies Quarterly 42(3):577-96 (2012).


“Separated Powers in the United States,” (with Joshua D. Clinton, Anthony M. Bertelli, Christian Grose, and David C. Nixon). American Journal of Political Science 56(2):341-54 (2012).


The Consequences of Presidential Patronage for Agency Performance,” (with Nick Gallo). Journal of Public Administration Research and Theory.  22(2): 219-243 (2012).

Complete_PART_Score_Data 122109

STATA batch file


Modern Presidents and the Transformation of the Federal Personnel System,” The Forum, 7(4): Article 6 (2010).

growth in appointees


Expert Opinion, Agency Characteristics, and Agency Preferences,” (with Joshua D. Clinton). Political Analysis 16(1):3-16 (2008)

Persons interested in replicating this analysis should also see Joshua Clinton’s web page which includes R code and data in txt format (http://www.princeton.edu/~clinton/datacode.html).

Data:

Raw data (Expert Survey Data 0707)

Codebook (clinton-lewis codebook)

Sample survey (expertsurvey3)

Additional materials:

Agency preferences estimates (Estimates of Agency Preferences 0707).


Management and Leadership Performance in the Defense Department: Evidence from Surveys of Federal Employees.” (with Major Paul S. Oh, U.S. Army) Armed Forces and Society 34(4): 639-661 (2008)

Data for this project comes from the Partnership for the Public Service and was obtained under special agreement with them. Interested parties should contact them directly for the data. Data from the Partnership was supplemented with information from OPM’s Fedscope website and publicly available biographical information for the DOD managers.

Stata batch file, Stata output (militaryleadership.do-militaryleadership.smcl)

Additional materials:

Web appendix for the paper (Web-appendixAFS)


“Testing Pendleton’s Premise: Do Political Appointees Make Worse Bureaucrats?” Journal of Politics 69(4):1073-88 (2007).

PART Scores Data:

Data by program: This dataset includes data on all federal programs graded by the Office of Management and Budget (OMB) as part of their budget-performance integration initiative in the FY 2004-2006 federal budgets. OMB has graded 614 programs since the Bush Administration’s initiative began in 2002 (for the FY 2004 budget).  They have graded approximately 200 programs each year (234, 175, 206).  Each program is one observation in the data.  Although programs graded for the first time in 2002 and 2003 have been regraded in subsequent years, this dataset includes programs only for the first year they were graded.  Programs are located in different bureaus across the federal government, some within a cabinet department and some located in independent agencies.

Codebook (PART Management Grades Dataset)

Data in Excel format (indepthmgt070906)

Data in Stata format (indepthmanagement070906.dta)

Time-varying covariates: To execute the batch file below, the PART data has to be merged with a dataset of time-varying variables. This dataset simply includes information about political conditions from year to year such as the presence of divided government, the existence of a war, the presence of a new administration, etc.

Time-varying covariates in Stata format (mgttvc.dta)

Stata batch files:

Stata batch file (bureauchief1.do)

Additional materials:

Web appendix for paper (webappendixjop)



Political Appointments, Civil Service Systems, and Bureaucratic Competence: Organizational Balancing and Gubernatorial Revenue Forecasts in the American States.” (with George Krause and James Douglas) American Journal of Political Science 50(3):770-87 (2006).

The following data and batch files will provide the means of replicating the analyses in this paper. The data, batch files, and output for a number of auxiliary analyses are also included below.

Stata data file (orgbalancing.10-07-05.dta)

Data codebook (KLD Codebook)

Stata batch file for analysis in tables 1-4 (MeritApptSystem.Timewise.Tables1-4.7-29-05.do)

Stata output for analysis in tables 1-4 (MeritApptSystem.Timewise.Results.Tables1-4.7-29-05.smcl)

Additional files:

Data (excluding certain cases)

batch-files (for auxiliary analyses)

output (for auxiliary analyses)


Assessing Performance Assessment for Budgeting: The Influence of Politics, Performance, and Program Size in FY 2005.” (with John B. Gilmour) Journal of Public Administration Research and Theory, 16(2):169-86 (2006).

The following data and batch files will provide the means of replicating the analyses in this paper.

There are two errors in the published version of the paper that should be noted. First, in Figure 2 the top two histograms are incorrectly labeled as reflecting “FY 2050” Data rather than FY 2005 data.

Second, the estimates from first model in Table 3 are for a percentage change in the budget from FY 2003 to FY 2004 rather than FY 2004 to FY 2005 as suggested by the table’s title. Commands to estimate models both for the FY 2003 to FY 2004 and FY 2004 to FY 2005 data are included in the batch file below.

Cohort 1 (Programs graded for the first time in the FY 2004 budget)

First cohort PART score data (cohort1jpart.dta)

Second set of PART scores for the first cohort (cohort1jpartfy2005scores.dta)

Stata batch file for cohort 1 (cohort1jpart.do)

Time-varying covariates (gilmourtv.dta)

cohort-2

Second cohort PART score data (cohort2jpart.dta)

Additional data for this cohort (cohort2jpartfix.dta)

Stata batch file for cohort 2 (cohort2jpart.do)


Political Appointees and the Competence of Federal Program Management.” (with John B. Gilmour) American Politics Research, 34(1):22-50 (2006).

Files

Data in Stata format (partscores060803.dta)

Time-varying covariates (gilmourtv.dta)

Stata batch file (management.do)


Staffing Alone: Unilateral Action and the Politicization of the Executive Office of the President, 1988-2004.” Presidential Studies Quarterly, 35(3):496-514 (2005).

Data in Excel format (psqeop031105)

Time-varying covariates (economictv2)

Stata batch file for basic analysis in Table 1 (psqpub.do)


The Adverse Consequences of the Politics of Agency Design for Presidential Management in the United States: The Relative Durability of Insulated Agencies.” British Journal of Political Science, 34(3):377-404 (2004).

The empirical analysis included in this piece is conducted using the Event File dataset (APDesignSpellData.xls) described above with one additional variables. The dataset for the paper can be reconstructed using the APDesignSpellData.xls file above and adding the additional variables by hand but I would recommend using the data files attached below in both Stata (.dta) and Excel (.xls) formats which include the relevant changes. The columns are in a different order than APDesignSpellData.xls but the variables are the same except for a few new variables. The most prominent additional variable is one that codes for whether an agency is a regulatory agency or not (warrenreg). It has the following source:

Warren, Melinda. 2000. Federal Regulatory Spending Reaches a New Height: An Analysis of the Budget of the U.S. Government for the Year 2001. St. Louis, MO: Center for the Study of American Business, Washington University; USGM. I code all agencies listed in the Center for the Study of American Business report as agencies with regulatory functions.

I have attached the batch file I used in Stata for the analyses. The batch file (insuldur1.do) drops agencies 10329 and 10439 which are courts but does not drop the courts in the cabinet departments (10152 and 10458). The dataset used for the paper (durdata51.dta) is missing 7 additional observations. The 7 observations are from agency 10469 which is the Administration for Children and Families (ACF). Unfortunately, I cannot recall the reason why ACF is excluded.

Files

Data in Excel format (durdata51.xls)

Data in Stata format (durdata51.dta)

Stata batch file (insuldur1.do)


Political Learning from Rare Events: Poisson Inference, Fiscal Constraints and the Lifetime of Bureaus.” (with Daniel C. Carpenter). Political Analysis, 12(3):201-32 (2004).

The empirical analysis included in this piece is conducted using the Event File dataset (APDesignSpellData.xls) described above with three changes:

1) We took advantage of updates made to the dataset described above. In particular, we drop agencies that now appear as if they should have been excluded and we recode some agencies as created by executive action that were originally coded as created by statute (see Updates and Notes above). We also fix an error in the start data for the Administration for Native Americans.

2) We added some additional variables including data on regulatory agencies and data on budget surpluses and deficits adjusted for inflation. The variables are described below:

1. warrenreg–Agencies with regulatory responsibilities. Warren, Melinda. 2000. Federal Regulatory Spending Reaches a New Height: An Analysis of the Budget of the U.S. Government for the Year 2001. St. Louis, MO: Center for the Study of American Business, Washington University; USGM. I code all agencies listed in the Center for the Study of American Business report as agencies with regulatory functions.
2. govrecpt—Federal revenues in billions of dollars.
3. surplusnom—nominal federal government surplus in billions of dollars.
4. urbancpi—Consumer price index for urban areas.
5. imfdeflt—International Monetary Fund price deflator to adjust nominal dollars to account for inflation.
6. pcchgcpi—Percentage change in the consumer price index.
7. pcchgimf—Percentage change in the IMF price deflator.
8. realsurplusimf—Federal surplus in real billions of dollars.

The source for the latter variables are: U.S. Department of Commerce. Bureau of the Census. Historical Statistics of the United States: Colonial Times to 1970. Washington, DC: Government Printing Office; Economic Report of the President. Various years. Washington, DC: Government Printing Office.

3) The data set drops all observations from temporary agencies (variable name: temporar—171 observations) and for courts (10439—16 observations; 10458—10 observations) with the exception of 10152 (US Court of Appeals for the Armed Forces) which was an oversight. The inclusion or exclusion of 10152 does not appear to alter the results.

The dataset for the paper can be reconstructed using the APDesignSpellData.xls file above and adding the additional variables by hand but I would recommend using the data files attached below in both Stata (.dta) and Excel (.xls) formats which include the relevant changes.

I have attached the batch file I used in Stata for the analyses.

Files

Data in Excel format (durdatacarp.xls)

Data in Stata format (durdatacarp.dta)

Stata batch file (carpenterpa1.do)


Agencies by Presidential Design.” (with William G. Howell) Journal of Politics 64(4): 1095-1114.

Data (DesignData)

Data for Figures (creationterminationdata4697)

Stata Batch File (jop1102.do)


The Politics of Agency Termination: Confronting the Myth of Agency Immortality.” Journal of Politics 64(1): 89-107.

Data (immortalityjopdata.xls)

Data for Figures (rawdatafig1fig2)

Stata Batch File (immortjop.do)


What Time is it? The Use of Power in Four Different Types of Presidential Time.” Journal of Politics 58(3): 687-706. (With James Michael Strime)

Data (veto)

Reports

Sourcebook of United States Executive Agencies. (with Jennifer L. Selin) Washington D.C., Administrative Conference of the United States

ACUS Sourcebook Codebook/Appendix (http://www.vanderbilt.edu/csdi/ACUSB.pdf)

ACUS Sourcebook Data ACUS0413

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David Lewis
PMB 505
230 Appleton Place
Nashville, TN 37203-5721
Telephone: 615-322-6228 (Central Time)
Fax: (615) 343-6003
david.e.lewis@vanderbilt.edu